Investigating Pure State Uniqueness in Tomography via Optimization
Jiahui Wu, Zheng An, Chao Zhang, Xuanran Zhu, Shilin Huang, Bei Zeng

TL;DR
This paper explores conditions for uniquely determining pure quantum states in tomography, introduces a unified optimization framework using ALM, and validates findings through numerical experiments on complex quantum systems.
Contribution
It develops a low-rank constrained optimization approach for pure state tomography, addressing computational challenges in UDA and UDP determinations.
Findings
Validated theoretical conditions with numerical experiments
Revealed the distribution of states across UDA, UDP, and neither categories
Proposed a practical method for quantum state uniqueness determination
Abstract
Quantum state tomography (QST) is crucial for understanding and characterizing quantum systems through measurement data. Traditional QST methods face scalability challenges, requiring measurements for a general -dimensional state. This complexity can be substantially reduced to in pure state tomography, indicating that full measurements are unnecessary for pure states. In this paper, we investigate the conditions under which a given pure state can be uniquely determined by a subset of full measurements, focusing on the concepts of uniquely determined among pure states (UDP) and uniquely determined among all states (UDA). The UDP determination inherently involves non-convexity challenges, while the UDA determination, though convex, becomes computationally intensive for high-dimensional systems. To address these issues, we develop a unified framework…
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Taxonomy
TopicsReservoir Engineering and Simulation Methods · Medical Imaging Techniques and Applications · Advanced X-ray and CT Imaging
